I am. Using .NET Core 3.1 for quite a while to run the "batch like" jobs that get kicked off when events happen in my system (file upload in S3 -> event -> Lam

I am. Using .NET Core 3.1 for quite a while to run the "batch like" jobs that get kicked off when events happen in my system (file upload in S3 -> event -> Lambda to process it). Plus a few other things, basically anything that I needed some kind of asynchronous processing to occur. The upside for me is the system is "sorta serverless" - the main website is a Docker container that has a .NET Core 3.1 web service in it. This is now setup so that a simple "dotnet ecs deploy-service" copies the container up to AWS, and triggers the load balancer setup etc. without me having to do anything. Similarly the Lambda functions are deployed with "dotnet lambda deploy-function" that just replaces the existing function. Obviously this is all more complicated than doing stuff with Python, but the ability to have a single .NET library that access all my stuff, but can be executed within the Docker container or executed as part of a Lambda function makes developing an absolute breeze. There don't seem to be any downsides to using .NET for this compared to anything else. Throw in S3 for file storage and AuroraDB as a shared database and you have something that doesn't cost a bomb to run (Aurora is the most expensive bit), is wicked fast on minimal requested hardware and bonkers reliable. The only real downside is that Lambda functions are a bit hard to do testing/debugging on but there are localised execution tools you can use to simulate AWS events that trigger Lambdas. Overall I've been surprised how good it turned out to be. I originally envisaged my system to be running on a dedicated server but this is much, much better.